Full Jev Tutorial What it is, how you can build with it and what new applications it can unlock → 0:00 Intro → 0:34 Jev explained → 4:06 API setup → 5:59 Demo 1: Voice-controlled browser → 11:33 Demo 2: AI memory → 17:27 Demo 3: YouTube predictor
Unclutter
WXT Chrome and Firefox extension that has Jev classify nonessential page elements through TypeSafe or Vercel AI Gateway, then stores reusable local hiding rules by page template. Paid analysis is manual by default, with an optional on-visit mode.
- Category
- Tools & Integrations
- Published by
- Community
- Author
- kitze
- Added
- 2026-09-22
Tagscommunitytypescriptchrome-extensionbrowserclassification
Highlights
- Jev classifies bounded page-element snippets through TypeSafe or Vercel AI Gateway.
- Hiding rules are stored locally and reapplied by page template, so they work offline.
- Manual analysis is the default; on-visit analysis is optional and sends snippets to the provider.
- WXT builds for Chrome and Firefox from one codebase; Bun and Node 22.12+ are required.
- The API key stays in local extension storage and is never sent to page content scripts.
Quickstart
bash
git clone https://github.com/kitze/unclutter.git
cd unclutter
bun install --frozen-lockfile
bun run build
# load .output/chrome-mv3 as an unpacked extensionWatch out
MIT-licensed. Requires Bun and Node 22.12+ to build, plus a Vercel AI Gateway or TypeSafe key; the key stays in local extension storage unencrypted, and saved rules keep working offline without it.
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From the community
Posts from builders shipping with Jev right now.
Full Jev video tutorial
The case against Jev-scored compaction
This is a terrible compaction strategy that fundamentally doesn't understand how compaction and context management work. Seems like a lot of people are confused so let's break this down. 1. Compaction isn't a filter The role of compaction is to clean up history to keep the Show more
found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
Classifying rows in DuckDB
I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!
A playable 16-judgment demo
typesafe's jev is fun! live demo you can play with: typesafe-demo.val.run
AI multiple choice, not essay writing
WTF is Jev by @typesafeai? Here’s the tl;dr ELI5: Think AI multiple choice, not AI essay writing. It doesn’t chat. It makes decisions your software can act on: “Spam or not?” “Which tool should this agent use?” “Does this need a human?” The exciting part: roughly 200x faster Show more
Screening agent actions with Jev
Tested TypeSafe’s Jev (no-text, probability-only model) as an AI agent safety monitor. Checking each action first worked well caught most attacks with almost no false blocks, and much faster than Gemini.
@CompleteSkeptic
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x